Estimation of Premorbid Intelligence Quotient of the Intelligence Scale for Chinese Adult

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1 ,2 1, (1., ; 2., ) : : (ISCA), : R %- 86.6%, , , 49.9%-67.8% : ISCA 10 ISCA ; ; ; : R395.1 : A : (2012) Estimation of Premorbid Intelligence Quotient of the Intelligence Scale for Chinese Adult TANG Xi-rong, YAO Shu-qiao Medical Psychological Institute,Second Xiangya Hospital,Central South University,Changsha , China Abstract Objective: To explore estimating IQ of the Intelligence Scale for Chinese Adult(ISCA). Methods: Standardized sample of the ISCA(n=2035) was roughly equally divided, at random, into two groups, one for development of the estimating formulae and the other for validation. A series of hierarchical linear regression analyses were carried out to develop formulae for estimating intelligence quotient. In the procedure, demographic variables, including age, education, gender, vocation, ethnicity and region of the country, as well as performance of hold subtests were predictors. To validate those formulae, comparison between the estimated IQ s and actual IQ s were executed. Results: There was no significant difference between the demographic characteristics and test scores of the two groups. Ten estimating formulae were developed, of which adjusted R 2 was 38.3%-86.6%, estimating standard error was There was no significant difference between the mean of estimated IQ s and actual IQ s, while ranges of estimated IQ s were more limited than those of actual IQ s in different measures. Estimated and actual values showed high correlation of and shared same IQ grades at ratio of 49.9%-67.8%. Estimation of combining performance of subtest and demographic variables showed more satisfactory validitied than that of demographic variables simply. However, the more subtests employed, the less each subtest contribute. Conclusion: Based on the data of the ISCA standardization sample, ten ISCA IQ estimating formulae were developed, they all show satisfied validity of estimation in intact adults. Key words Intelligence scale for Chinese adult; Intelligence quotient; Premorbid intelligence; Validity [2,3] (promorbid intelligence),,,, [4],, [5,6] [1] :, ;,,,, ;, (2008-B61) : [1]

2 744 Chinese Journal of Clinical Psychology Vol. 20 No , : =1 =0; ; :0= 3 1= 6 2= 9 3= [4] 12 4= >12,,, [7-9] ; : =1 =0; [10,11] ( ) (ISCA), [12] [13,14], ISCA Schoenberg [9], ISCA, : ISCA,,,, 1, 1.1 ISCA 2035,,,, 1008, 1027 ;, 16-92, 12 ; 2000,, ;,,, [13,14], 1.2 ISCA 12 :,,, 6, 6, ;, ISCA , SPSS, Pearson 50% ISCA ( ),, (70 ( ) ) (70-79) (80-89) (90-109) ( ) ( ) (130 ) 10, : Friedman

3 SPSS15.0, 2 (F=1.34,P=0.25) , 2.2, %, 38.3%, , R , (χ 2 =, 64.3%-67.8%, ,P=0.71) 41.14±20.65, 41.62±20.81 (F=0.15,P=0.69) 51.7%-58.1%, R ± ±4.07, 74.4%-78.2%, , 5.47, (χ 2 =0.52,P=0.47),, ( 1), (F=0.58,P=0.71) 1! "# $ #! # #! % $ # "! % ##! " & "! $ $! # (! % $$ #! % #"! ( ( 2 : (%) R 2 Á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

4 746 Chinese Journal of Clinical Psychology Vol. 20 No , 35.6%-53.5% ( P=0.07), ( r 0.62,P=0.00), 2 R 2 ;, 13 ;,, ,49.9%-, 67.8%, 13.9%- 65 [13,14] 0.91%, (χ 2 =1.92, df=3,p=0.59), 60% (χ 2 =2.72,df=3,P=0.44); 0.8, 3, (χ 2 =61.76,df=4,P=0.00) 5%, (χ 2 =88.26,df=7,P=0.00) (χ 2 =50.12,df=4,P=0.00),, R 2, 3,,,, [8], 28.6%, R , 0.62,, [2,3] 49.1%, IQ IQ ,, ,,, 23.1%, [13] 5.47, ISCA, 0.33, [8] Schoenberg, [3],,ISCA : [13,14], ; [15], ISCA 100, ISCA, R 2

5 ,. :. adolescents using the American Wechsler intelligence scale,2002,10(4): for children-fourth edition: Demographic and current performance 2 Wilson RS, Rosenbaum G, Brown G, et al. An index of premorbid intelligence. J Consult Clin Psychol, 1978, 46 (6): approaches. J Child Neurol, 2007, 22(4): Vanderploeg RD. WISC-III premorbid prediction strategies: Demographic and best performance approaches. Psychological 3 Assessment, 1998, 10(3): ,..,1993,18(2): Vanderploeg RD. Estimation of WAIS-R premorbid intelligence: 4 Franzen MD, Burgess EJ, Smith -Seemiller L. Methods of estimating premorbid functioning. Arch Clin Neuropsychol, 1997, 12(8): Current ability and demographic data used in a best- performance fashion. Psychological Assessment, 1996, 8(4): ,,. 12,,,..,2007,15(2): ,120 6 Barker-Collo S, Bartle H, Clarke A, et al. Accuracy of the national adult reading test and spot the word estimates of premorbid intelligence in a non-clinical New Zealand sample. New Zealand Journal of Psychology, 2008, 37(3): Vanderploeg RD, Schinka JA. Predicting WAIS-R IQ premorbid ability: Combining subtest performance and demographic variable predictors. Arch Clin Neuropsychol, 1995, 10(3): Schoenberg MR, Scott JG, Duff K, et al. Estimation of WAIS-III intelligence from combined performance and demographic variables: development of the OPIE -3. Clin Neuropsychol, 2002, 16(4): Schoenberg MR, Lange RT, Brickell TA, et al. Estimating premorbid general cognitive functioning for children and.,2006,14(5): ,,,..,2007,21(1): ,,..,2009,17(5): Schoenberg MR, Scott JG, Ruwe W, etc. Assumptions that underlie predicting premorbid IQ: A comment on the evaluation of the accuracy of two regression-based methods for estimating premorbid IQ. Arch Clin Neuropsychol, 2004, 19(8): ( : )!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ( 776 ) ation are unattended. Neuroscience Letters, 2011, doi: Mocaiber I, Pereira MG, Erthal FS, et al. Fact or fiction? 1016/j.neulet An event-related potential study of implicit emotion regulation. Neuroscience Letters, 2010, 476(2): 84-88,2005,19(11): ,,,.. 12 Cuthbert BN, Schupp HT, Bradley MM, et al. Brain potentials in affective picture processing: Covariation with autotients of late -onset depression revealed by ERP study. 19 Zhang BW, Xu J, Zhao L. Emotion regulation deficit in panomic arousal and affective report. Biological Psychology, Space Medicine and Medical Engineering, 2006, 19: , 52: MacNamara A, Foti D, Hajcak G. Tell me about it: Neural 20 Hajcak G, Dennis TA. Brain potentials during affective picture viewing in children. Biological Psychology, 2009, 80: activity elicited by emotional pictures and preceding de scriptions. Emotion, 2009, 9(4): Hajcak G, Nieuwenhuis S. Reappraisal modulates the electrocortical response to negative pictures, Cognitive, Affec- 14 Fruhholz S, Jellinghaus A, Herrmann M.Time course of implicit processing and explicit processing of emotional faces tive, and Behavioral Neuroscience, 2006, 6: and emotional words. Biological Psychology, 2011, doi: Birn RM, Smith MA, Jones TB, et al. The respiration response function: The temporal dynamics of fmri. Neuro /j.biopsycho Hajcak G, Dunning JP, Foti D. Motivated and controlled attention to emotion: Time-course of the late positive poten- 23,,,. Image, 2008, 40: tial. Clinical Neurophysiology, 2009, 120: ,2010,18(2): 16 Moser JS, Hajcak, G, Bucay E, et al. Intentional modulation of emotional responding to unpleased pictures: An ERP 24,,. BPD study. Psychophysiology, 2006, 43: ,2010,18(4): Wiens S, Sand A, Norberg J, et al. Emotional event-related 425 potentials are reduced if negative pictures presented at fix- ( : )

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